Camera location estimation is a very valuable process for automated robotic devices that autonomously move through an environment, as the robotic device must be aware of both its surroundings and its own location within the environment. Recent outlier-robust methods have been proposed for camera location estimation. One class of solvers uses outlier detection algorithms as a preprocessing step to improve their subsequent estimator. One such algorithm is the 1DSfM algorithm. The 1DSfM algorithm projects three-dimensional (3D) pairwise direction vectors onto one-dimensional (1D) vectors, and reformulates the cycle-consistency constraints as an ordering problem and solves it using a heuristic combinatorial method. Another class of methods directly solve robust convex optimization problems and include the least unsquared deviations (LUD) algorithm and the ShapeFit algorithm.